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Towards Trust-Aware IoT Hashing Offloading in Mobile Edge Computing | IEEE Conference Publication | IEEE Xplore

Towards Trust-Aware IoT Hashing Offloading in Mobile Edge Computing


Abstract:

The massive increase of IoT connected devices is imposing various challenges at different dimensions due to the constrained capabilities of devices and huge requirements ...Show More

Abstract:

The massive increase of IoT connected devices is imposing various challenges at different dimensions due to the constrained capabilities of devices and huge requirements of applications. Attributed to the benefits it offers in terms of time and cost, pushing security solutions to the network edge has attracted tremendous interest. Most of the hashing algorithms are centralized focusing on optimizing hashing techniques while considering enough processing and power capabilities. However, hashing algorithms in the context of IoT world suffer from the limitations of devices in terms of battery power and computing capabilities, thus distributed hashing becomes a necessity to enable it within IoT environment. In this paper, we introduce a trust-aware based model that provides efficient and trusted distribution of hashing computation among mobile edge resources. We formulate the distribution model as an integer linear programming problem while taking into consideration various parameters and constraints. Experimental results explore the efficiency of our proposed approach with respect to the literature.
Date of Conference: 15-19 June 2020
Date Added to IEEE Xplore: 27 July 2020
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Conference Location: Limassol, Cyprus

I. Introduction

Internet of things (IoT) is pertaining to every branch of our lives. The architecture of IoT devices make it rapidly extend to a big number of fields including health monitoring, greenhouse monitoring, as well as traffic management in smart transportation. However, the pervasive flow of IoT devices in different fields comes along with significant challenges, one of which is ensuring security along different dimensions [1], [2]. IoT devices are vulnerable to a wide range of attacks including data tampering, eavesdropping and physical attacks [3]. While data tampering may incur severe losses, ensuring data integrity prevents data modification from source to destination and increases the security level. Integrity of this data comes with high importance to achieve an accurate flow of data over its entire life-cycle [4] and thus increases the outcomes of the IoT ecosystem. Hashing has been one of the effective and traditional techniques used to ensure integrity of data. For example, an IoT device may send large amount of data but it needs the data sent in public not to be modified or altered on the way to the destination [5]. However, applying traditional security solutions to achieve the integrity of large sizes of data generated by IoT devices becomes unfeasible due to their limited resources.

References

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